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Total 292 records

    Model Checking of Priced Timed Activity Networks

    , M.Sc. Thesis Sharif University of Technology Esmaili, Mohammad Esmail (Author) ; Movaghar Rahimabadi, Ali (Supervisor)
    Abstract
    Verification of timed systems is concerned by many researchers in the last decades because of using these systems in critical applications. So, several models such as Timed Automat (TA) and Time Petri Nets (TPN) have been proposed for modeling these systems and variety of logics and abstraction methods are defined. One of the significant problems in timed system is cost-optimal reachability problem where, given an initial state and a target state, the task is to comput a path with infimum cost from initial state to the target state. Priced Timed Automat (PTA) introduce for solving cost-optimal reachability problems such as optimal scheduling and planing in timed systems. PTA is defined as an... 

    Using Game Theory to Model Covering and Packing Problems

    , M.Sc. Thesis Sharif University of Technology Gheibi, Omid (Author) ; Zarrabi-Zadeh, Hamid (Supervisor)
    Abstract
    Game theory is widely used to model diverse phenomena in the real world such as people’s behavior in elections and auctions. It also has natural applications to some other areas such as computer networks, cryptography, and security. In this thesis, we present a general approach to model two important classes of optimization problems, namely, covering and packing problems, using game theory concepts. This model provides an integrated language to explain the problems, and enables us to use game-theoretic tools to further explore and analyze the problems. In our proposed model, the optimum solutions of the modeled problem are always one of the equilibria of the game. Therefore, one can find... 

    Coordinated Strategy of Price-maker Renewable Generation and Thermal Units in Elrctricity Market

    , M.Sc. Thesis Sharif University of Technology Goodarzi, Hamed (Author) ; Ranjbar, Ali Mohammad (Supervisor)
    Abstract
    Wind energy, as a type of renewable energy resource, is clean and is rapidly growing globally. The intermittency in the production of wind energy is the most major obstacle for these producers in a competitive electricity market, to compete with thermal units. Most existing models in the literature mitigate the risk of wind power, by coordinating them with energy storages such as pumped storages power plant. Here, in this thesis, another risk mitigation approach is introduced which combines wind energy and natural gas power plant in an electricity market. In addition, as the penetration level of wind power grows, the wind power producers must be considered as a price-maker player which their... 

    Optimal Coherent Control of Quantum Dynamics: Process-Based Approach

    , Ph.D. Dissertation Sharif University of Technology Rezvani, Vahid (Author) ; Rezakhani, Ali (Supervisor)
    Abstract
    One of the main tools of the developing quantum technology is making the desired quantum gates and processes in the presence of the environmental noises. In this thesis, we first derive a Markovian master equation which defines purely the time evolution of the dynamics (process matrix) of the open system rather than its state (density matrix). This master equation indeed describes the time evolution of the Choi-Jamiolkowsli matrix which is independent of the state of the system at all times including the initial state. The n, by using this master equation we provide a scheme to manipulate optimally and locally the dynamics of the open system by external coherent agents. Such scheme... 

    Waveform Design for Interference Mitigation in SAR Imaging and Sparse Image Recovery

    , M.Sc. Thesis Sharif University of Technology Keyhani, Erfan (Author) ; Karbasi, Mohammad (Supervisor)
    Abstract
    In this research, we design a compatible waveform for the purpose of high-quality synthetic aperture radar (SAR) imaging in conjunction with sparse recovery methods for image formation. The goal is to make the imaging system tolerable against the wide-band and narrowband electromagnetic interferences. Actually, we consider minimizing the mutual interference between our radar and coexisting licensed emitters and minimizing the jamming signal (unlicensed emitters) power while enforcing some constraints over the waveform features like peak-to-average-power ratio (PAPR). For the constrained optimization problem to design a proper waveform, we introduce a new constraint to the optimization... 

    Model predictive control of nonlinear discrete time systems with guaranteed stability

    , Article Asian Journal of Control ; 2018 ; 15618625 (ISSN) Shamaghdari, S ; Haeri, M ; Sharif University of Technology
    Wiley-Blackwell  2018
    Abstract
    This paper presents the design of a new robust model predictive control algorithm for nonlinear systems represented by a linear model with unstructured uncertainty. The linear model is obtained by linearizing the nonlinear system at an operating point and the difference between the nonlinear and linear model is considered as a Lipschitz nonlinear function. The controller is designed for the linear model, which fulfills the stabilization condition for the nonlinear term. Unlike previous studies that have not considered a valid Lipschitz matrix of nonlinear term in the design process, we propose an algorithm in this paper in which it is considered. Therefore, the closed loop stability of the... 

    Model predictive control of nonlinear discrete time systems with guaranteed stability

    , Article Asian Journal of Control ; Volume 22, Issue 2 , 2020 , Pages 657-666 Shamaghdari, S ; Haeri, M ; Sharif University of Technology
    Wiley-Blackwell  2020
    Abstract
    This paper presents the design of a new robust model predictive control algorithm for nonlinear systems represented by a linear model with unstructured uncertainty. The linear model is obtained by linearizing the nonlinear system at an operating point and the difference between the nonlinear and linear model is considered as a Lipschitz nonlinear function. The controller is designed for the linear model, which fulfills the stabilization condition for the nonlinear term. Unlike previous studies that have not considered a valid Lipschitz matrix of nonlinear term in the design process, we propose an algorithm in this paper in which it is considered. Therefore, the closed loop stability of the... 

    An efficient approach for optimum shape design of steel shear panel dampers under cyclic loading

    , Article Smart Structures and Systems ; Volume 27, Issue 3 , 2021 , Pages 547-557 ; 17381584 (ISSN) Khatibinia, M ; Ahrari, A ; Gharehbaghi, S ; Sarafrazi, S. R ; Sharif University of Technology
    Techno-Press  2021
    Abstract
    The low-cycle fatigue performance of shear panel damper (SPD) highly depends on the geometry of its shape and the criterion considered for its design. The main contribution of the current study is to find the optimum shape of the SPD subjected to cyclic loading by considering two different objective functions. The maximum equivalent plastic strain and the ratio of energy dissipation through plastic deformation to the maximum equivalent plastic strain are selected as the first and second objective functions, respectively. Since the optimization procedure requires high computational efforts, a hybrid computational approach is used to perform two paramount phases of estimating the inelastic... 

    A superlinearly convergent nonmonotone quasi-Newton method for unconstrained multiobjective optimization

    , Article Optimization Methods and Software ; Volume 35, Issue 6 , March , 2020 , Pages 1223-1247 Mahdavi Amiri, N ; Salehi Sadaghiani, F ; Sharif University of Technology
    Taylor and Francis Ltd  2020
    Abstract
    We propose and analyse a nonmonotone quasi-Newton algorithm for unconstrained strongly convex multiobjective optimization. In our method, we allow for the decrease of a convex combination of recent function values. We establish the global convergence and local superlinear rate of convergence under reasonable assumptions. We implement our scheme in the context of BFGS quasi-Newton method for solving unconstrained multiobjective optimization problems. Our numerical results show that the nonmonotone quasi-Newton algorithm uses fewer function evaluations than the monotone quasi-Newton algorithm. © 2020 Informa UK Limited, trading as Taylor & Francis Group  

    A robust simulation optimization algorithm using kriging and particle swarm optimization: application to surgery room optimization

    , Article Communications in Statistics: Simulation and Computation ; Volume 50, Issue 7 , 2021 , Pages 2025-2041 ; 03610918 (ISSN) Azizi, M. J ; Seifi, F ; Moghadam, S ; Sharif University of Technology
    Taylor and Francis Ltd  2021
    Abstract
    Simulation optimization is an endeavor to determine the best combination of inputs that result in the best system performance criterion without evaluating all possible combinations. Since simulation optimization applies to many problems, it is extensively studied in the literature with different methods. However, most of these methods ignore the uncertainty of the systems’ parameters, which may lead to a solution that is not robustly optimal in reality. Motivated by this uncertainty, we propose a robust simulation optimization algorithm that follows the well-known Taguchi standpoint but replaces its statistical technique with a minimax method based on the kriging (Gaussian process)... 

    On the assignability of LTI systems with arbitrary control structures

    , Article International Journal of Control ; 2021 ; 00207179 (ISSN) Babazadeh, M ; Sharif University of Technology
    Taylor and Francis Ltd  2021
    Abstract
    In this paper, the assignability of linear time-invariant (LTI) systems with respect to arbitrary control structures is addressed. It is well established that the closed-loop spectrum of an LTI system with an arbitrary control structure is confined to the set containing the fixed-modes of the system with respect to that control structure. However, the assignment of the closed-loop spectrum is not merely limited by the existence of fixed-modes in practical scenarios. The pole assignment may require excessive control effort or even become infeasible due to the presence of small perturbations in the system dynamics. To offer more insights in such more realistic scenarios, a continuous measure... 

    On the assignability of LTI systems with arbitrary control structures

    , Article International Journal of Control ; Volume 95, Issue 8 , 2022 , Pages 2098-2111 ; 00207179 (ISSN) Babazadeh, M ; Sharif University of Technology
    Taylor and Francis Ltd  2022
    Abstract
    In this paper, the assignability of linear time-invariant (LTI) systems with respect to arbitrary control structures is addressed. It is well established that the closed-loop spectrum of an LTI system with an arbitrary control structure is confined to the set containing the fixed-modes of the system with respect to that control structure. However, the assignment of the closed-loop spectrum is not merely limited by the existence of fixed-modes in practical scenarios. The pole assignment may require excessive control effort or even become infeasible due to the presence of small perturbations in the system dynamics. To offer more insights in such more realistic scenarios, a continuous measure... 

    Multi-objective economic-statistical design of simple linear profiles using a combination of NSGA-II, RSM, and TOPSIS

    , Article Communications in Statistics: Simulation and Computation ; Volume 51, Issue 4 , 2022 , Pages 1704-1720 ; 03610918 (ISSN) Roshanbin, N ; Ershadi, M. J ; Niaki, S. T. A ; Sharif University of Technology
    Taylor and Francis Ltd  2022
    Abstract
    A multi-objective economic-statistical design is aimed in this article for simple linear profiles. In this design, the interval between two successive sampling intervals, the sample size and the number of adjustment points alongside, the parameters of the monitoring scheme are determined such that not only the implementation cost is minimized, but also the profile exhibits desired statistical performances. To this aim, three objective functions are considered in the multi-objective optimization model of the problem. The Lorenzen–Vance cost function is used to model the implementation cost as the first objective function to be minimized. The second objective function maximizes the in-control... 

    Day-ahead resource scheduling in distribution networks with presence of electric vehicles and distributed generation units

    , Article Electric Power Components and Systems ; Volume 47, Issue 16-17 , 2019 , Pages 1450-1463 ; 15325008 (ISSN) Shafiee, M ; Ghazi, R ; Moeini Aghtaie, M ; Sharif University of Technology
    Taylor and Francis Inc  2019
    Abstract
    In this paper a new framework for scheduling of available resources in the distribution networks is developed. In this respect attempts are focused on interactions between charging/discharging profiles of electric vehicles (EVs) and output power of distributed generation units. To reach this goal, the proposed framework is designed as a two-stage optimization procedure. In the first stage, the charging/discharging schedules of EVs are extracted running a linear programing optimization problem taking into account the EV users' constraints and requirements. The usage profiles of the DG units, strategy of buying electricity from the market and also the final charging/discharging patterns of the... 

    A robust simulation optimization algorithm using kriging and particle swarm optimization: application to surgery room optimization

    , Article Communications in Statistics: Simulation and Computation ; 2019 ; 03610918 (ISSN) Azizi, M. J ; Seifi, F ; Moghadam, S ; Sharif University of Technology
    Taylor and Francis Inc  2019
    Abstract
    Simulation optimization is an endeavor to determine the best combination of inputs that result in the best system performance criterion without evaluating all possible combinations. Since simulation optimization applies to many problems, it is extensively studied in the literature with different methods. However, most of these methods ignore the uncertainty of the systems’ parameters, which may lead to a solution that is not robustly optimal in reality. Motivated by this uncertainty, we propose a robust simulation optimization algorithm that follows the well-known Taguchi standpoint but replaces its statistical technique with a minimax method based on the kriging (Gaussian process)... 

    A robust simulation optimization algorithm using kriging and particle swarm optimization: Application to surgery room optimization

    , Article Communications in Statistics: Simulation and Computation ; 2019 ; 03610918 (ISSN) Azizi, M. J ; Seifi, F ; Moghadam, S ; Sharif University of Technology
    Taylor and Francis Inc  2019
    Abstract
    Simulation optimization is an endeavor to determine the best combination of inputs that result in the best system performance criterion without evaluating all possible combinations. Since simulation optimization applies to many problems, it is extensively studied in the literature with different methods. However, most of these methods ignore the uncertainty of the systems’ parameters, which may lead to a solution that is not robustly optimal in reality. Motivated by this uncertainty, we propose a robust simulation optimization algorithm that follows the well-known Taguchi standpoint but replaces its statistical technique with a minimax method based on the kriging (Gaussian process)... 

    Simulation and optimization of pulsating heat pipe flat-plate solar collectors using neural networks and genetic algorithm: a semi-experimental investigation

    , Article Clean Technologies and Environmental Policy ; Volume 18, Issue 7 , 2016 , Pages 2251-2264 ; 1618954X (ISSN) Jalilian, M ; Kargarsharifabad, H ; Abbasi Godarzi, A ; Ghofrani, A ; Shafii, M. B ; Sharif University of Technology
    Springer Verlag  2016
    Abstract
    This research study presents an investigation on the behavior of a Pulsating Heat Pipe Flat-Plate Solar Collector (PHPFPSC) by artificial neural network method and an optimization of the parameters of the collector by genetic algorithm. In this study, several experiments were performed to study the effects of various evaporator lengths, filling ratios, inclination angles, solar radiation, and input chilled water temperature between 9:00 A.M. to 5:00 P.M., and the output temperature of the water tank, which was the output of the system, was also measured. According to the input and output information, multilayer perceptron neural network was trained and used to predict the behavior of the... 

    Investigation of trunk muscle activities during lifting using a multi-objective optimization-based model and intelligent optimization algorithms

    , Article Medical and Biological Engineering and Computing ; Volume 54, Issue 2-3 , 2016 , Pages 431-440 ; 01400118 (ISSN) Ghiasi, M. S ; Arjmand, N ; Boroushaki, M ; Farahmand, F ; Sharif University of Technology
    Springer Verlag  2016
    Abstract
    A six-degree-of-freedom musculoskeletal model of the lumbar spine was developed to predict the activity of trunk muscles during light, moderate and heavy lifting tasks in standing posture. The model was formulated into a multi-objective optimization problem, minimizing the sum of the cubed muscle stresses and maximizing the spinal stability index. Two intelligent optimization algorithms, i.e., the vector evaluated particle swarm optimization (VEPSO) and nondominated sorting genetic algorithm (NSGA), were employed to solve the optimization problem. The optimal solution for each task was then found in the way that the corresponding in vivo intradiscal pressure could be reproduced. Results... 

    Solving fuzzy quadratic programming problems based on ABS algorithm

    , Article Soft Computing ; Volume 23, Issue 22 , 2019 , Pages 11343-11349 ; 14327643 (ISSN) Ghanbari, R ; Ghorbani Moghadam, K ; Sharif University of Technology
    Springer Verlag  2019
    Abstract
    Recently, Ghanbari and Mahdavi-Amiri (Appl Math Model 34:3363–3375, 2010) gave the general compromised solution of an LR fuzzy linear system using ABS algorithm. Here, using this general solution, we solve quadratic programming problems with fuzzy LR variables. We convert fuzzy quadratic programming problem to a crisp quadratic problem by using general solution of fuzzy linear system. By using this method, the crisp optimization problem has fewer variables in comparison with other methods, specially when rank of the coefficient matrix is full. Thus, solving the fuzzy quadratic programming problem by using our proposed method is computationally easier than the solving fuzzy quadratic... 

    An extension of ant colony system to continuous optimization problems

    , Article 4th International Workshop on Ant Colony Optimization and Swarm Intelligence, ANTS 2004, Brussels, 5 September 2004 through 8 September 2004 ; Volume 3172 LNCS , 2004 , Pages 294-301 ; 03029743 (ISSN); 3540226729 (ISBN); 9783540226727 (ISBN) Pourtakdoust, S. H ; Nobahari, H ; Sharif University of Technology
    Springer Verlag  2004
    Abstract
    A new method for global minimization of continuous functions has been proposed based on Ant Colony Optimization. In contrast with the previous researches on continuous ant-based methods, the proposed scheme is purely pheromone-based. The algorithm has been applied to several standard test functions and the results are compared with those of two other meta-heuristics. The overall results are compatible, in good agreement and in some cases even better than the two other methods. In addition the proposed algorithm is much simpler, which is mainly due to its simpler structure. Also it has fewer control parameters, which makes the parameter settings process easier than many other methods. © 2004...